Results 111 to 120 of about 6,422 (208)

SuperCoT-X: Masked Hyperspectral Image Modeling With Diverse Superpixel-Level Contrastive Tokenizer

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Hyperspectral images (HSI) exhibit complex contextual relationships, including variations in local homogeneous regions and spectral similarities among different classes.
Miaomiao Liang, Weigang Wu, Huifang Shen, Lingjuan Yu, Xiangchun Yu, Licheng Jiao   +5 more
doaj   +1 more source

Corrosion defect segmentation method based on superpixel feature cascade

Ain Shams Engineering Journal
To solve the segmentation problem caused by the small number of feature points and the change of image brightness on the surface of the storage tank, a corrosion defect segmentation method based on the superpixel feature cascade is proposed in this paper.
Lingyu Sun, Yang Li, Xinbao Li, Chengyan Liu   +3 more
doaj   +1 more source

Joint superpixel and Transformer for high resolution remote sensing image classification

Scientific Reports
Deep neural networks combined with superpixel segmentation have proven to be superior to high-resolution remote sensing image (HRI) classification. Currently, most HRI classification methods that combine deep learning and superpixel segmentation use ...
Guangpu Dang, Zhongan Mao, Tingyu Zhang, Tao Liu, Tao Wang, Liangzhi Li, Yu Gao, Runqing Tian, Kun Wang, Ling Han   +9 more
doaj   +1 more source

Adaptive Superpixel Segmentation-Based Coastline Extraction Method for PolSAR Images

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
To improve the accuracy of coastline extraction for polarimetric synthetic aperture radar (PolSAR) images, an adaptive superpixel segmentation-based method is proposed.
Yu Wang, Zhanying Ma, Mengmeng Li, Yu Li, Xue Shi, Xuemei Zhao   +5 more
doaj   +1 more source

Unsupervised instance segmentation with superpixels

Pattern Recognition
Instance segmentation is essential for numerous computer vision applications, including robotics, human-computer interaction, and autonomous driving. Currently, popular models bring impressive performance in instance segmentation by training with a large number of human annotations, which are costly to collect.
openaire   +3 more sources

Superpixel Salient Object Detection

Salient object detection (SOD) is a core problem in computer vision that involves identifying and segmenting the most visually prominent regions in an image.
Park, Jinman
core  

FedSPGrad: Semantic-Superpixel Adaptive Perturbation for PrivacyPreserving Federated Image Learning

FedSPGrad: Semantic-Superpixel Adaptive Perturbation for PrivacyPreserving Federated Image Learning• Semantic superpixel scoring allocates perturbation by regional importance.• SLIC and Grad-CAM link visual saliency to feature confusion andGaussian noise.
Zhimin Wang, Renhao Hu, Qingshui Xue, Hao Jin, Kangxin Li, Lijun Liu, Haifeng Ma   +6 more
core   +1 more source

Vision-Based Automated Inspection of Box Meals for Food Portion Defects and Foreign Object Detection. [PDF]

Sensors (Basel)
Lin HD, Chen GM, Lin CH.
europepmc   +1 more source

Multi-class semantic segmentation of oral cancer tissues on whole-slide images: A SuperPixel enhanced deep learning approach. [PDF]

J Pathol Inform
León F, Champagnac A, Dupoy M, Fayette JM, Csűry TD, Duraffourg L, Saintigny P.   +6 more
europepmc   +1 more source

SLIC Superpixels

, 2010
Superpixels are becoming increasingly popular for use in computer vision applications. However, there are few algorithms that output a desired number of regular, compact superpixels with a low computational overhead. We introduce a novel algorithm that clusters pixels in the combined five-dimensional color and image plane space to efficiently generate ...
Achanta, Radhakrishna, Shaji, Appu, Smith, Kevin, Lucchi, Aurélien, Fua, Pascal, Süsstrunk, Sabine   +5 more
openaire   +1 more source